Update README.md

README.md

@@ -47,19 +47,31 @@ Our approach simplifies math dataset creation:
 
 This dataset contains web-crawled text data with comprehensive metadata, quality signals, and taxonomic classifications. Each record represents a document extracted from web archives with detailed provenance tracking and quality assessment metrics.
 
+## Core Fields
+
+| Field | Type | Description | Path |
+|-------|------|-------------|------|
+| `id` | `Int64` | Unique identifier for each document | `id` |
+| `text` | `String` | The main textual content of the document | `text` |
+
 ## EAI Taxonomy Classification
 
-Comprehensive hierarchical classification system with primary and secondary labels - the most important feature of this dataset:
+Comprehensive hierarchical classification system with primary and secondary labels - the most important feature of this dataset. The taxonomy is designed to provide detailed subject categorization, document type identification, content quality assessment, and extraction quality indicators.
 
 <details>
-<summary><strong>Free Decimal Correspondence</strong></summary>
+<summary><strong>Free Decimal Correspondence (FDC)</strong></summary>
+
+A Dewey Decimal-inspired classification system with 3-level hierarchical labels. The FDC provides nested categories where each successive level refines its parent category. It's designed to be compatible with the Dewey Decimal System for library cataloging.
 
-Dewey Decimal-inspired classification with 3-level hierarchical labels:
+**Level Structure:**
+- **Level 1**: Top-level categories (0-9) covering broad subject areas like General works, Philosophy, Religion, Social Sciences, etc.
+- **Level 2**: Sub-divisions (00-99) that refine Level 1 categories
+- **Level 3**: Specific categories (000-999) that further refine Level 2 categories
 
 | Component | Description | Path |
 |-----------|-------------|------|
 | Primary Code | Main classification code | `eai_taxonomy.free_decimal_correspondence.primary.code` |
-| Primary Level 1 | Top-level category | `eai_taxonomy.free_decimal_correspondence.primary.labels.level_1` |
+| Primary Level 1 | Top-level category (0=General works, 1=Philosophy, 2=Religion, 3=Social Sciences, 4=Language, 5=Science, 6=Technology, 7=Arts, 8=Literature, 9=History/Geography) | `eai_taxonomy.free_decimal_correspondence.primary.labels.level_1` |
 | Primary Level 2 | Mid-level category | `eai_taxonomy.free_decimal_correspondence.primary.labels.level_2` |
 | Primary Level 3 | Specific category | `eai_taxonomy.free_decimal_correspondence.primary.labels.level_3` |
 | Secondary Code | Alternative classification code | `eai_taxonomy.free_decimal_correspondence.secondary.code` |
@@ -74,8 +86,10 @@ We recommend this viewer for easily navigating the FDC categories when curating
 <details>
 <summary><strong>Bloom's Taxonomy Integration</strong></summary>
 
+Based on Anderson and Krathwohl's 2001 revision of Bloom's Taxonomy of Educational Objectives, providing two complementary categorization dimensions for educational content analysis.
+
 ### Cognitive Process
-Learning and thinking skill levels:
+Assesses the learning and thinking skill levels demonstrated by the document author:
 
 | Component | Description | Path |
 |-----------|-------------|------|
@@ -85,18 +99,18 @@ Learning and thinking skill levels:
 | Secondary Label | Alternative cognitive process label | `eai_taxonomy.bloom_cognitive_process.secondary.label` |
 
 **Possible Values:**
-| Code | Label |
-|------|-------|
-| `-1` | Abstain |
-| `1` | Remember |
-| `2` | Understand |
-| `3` | Apply |
-| `4` | Analyze |
-| `5` | Evaluate |
-| `6` | Create |
+| Code | Label | Description |
+|------|-------|-------------|
+| `-1` | Abstain | Unable to determine |
+| `1` | Remember | Retrieve relevant knowledge from memory |
+| `2` | Understand | Determine meaning of instructional messages |
+| `3` | Apply | Use a procedure in a given situation |
+| `4` | Analyze | Break materials into components and determine relationships |
+| `5` | Evaluate | Make judgments based on criteria and standards |
+| `6` | Create | Create new or original work |
 
 ### Knowledge Domain
-Subject matter categorization:
+Categorizes the type of knowledge demonstrated in the document:
 
 | Component | Description | Path |
 |-----------|-------------|------|
@@ -106,13 +120,13 @@ Subject matter categorization:
 | Secondary Label | Alternative knowledge domain label | `eai_taxonomy.bloom_knowledge_domain.secondary.label` |
 
 **Possible Values:**
-| Code | Label |
-|------|-------|
-| `-1` | Abstain |
-| `1` | Factual |
-| `2` | Conceptual |
-| `3` | Procedural |
-| `4` | Metacognitive |
+| Code | Label | Description |
+|------|-------|-------------|
+| `-1` | Abstain | Unable to determine |
+| `1` | Factual | Basic elements to learn or solve problems |
+| `2` | Conceptual | Interrelationships between basic elements within larger context |
+| `3` | Procedural | Methods and techniques in the discipline |
+| `4` | Metacognitive | Awareness of how learning works in relation to oneself |
 
 </details>
 
@@ -120,7 +134,7 @@ Subject matter categorization:
 <summary><strong>Document Characteristics</strong></summary>
 
 ### Document Type v1
-Format and structure classification:
+In-house classification of common web document types and formats:
 
 | Component | Description | Path |
 |-----------|-------------|------|
@@ -130,29 +144,29 @@ Format and structure classification:
 | Secondary Label | Alternative document type label | `eai_taxonomy.document_type_v1.secondary.label` |
 
 **Possible Values:**
-| Code | Label |
-|------|-------|
-| `-1` | Abstain |
-| `1` | News/Editorial |
-| `2` | Academic/Research |
-| `3` | Reference/Encyclopedic/Educational |
-| `4` | Code/Software |
-| `5` | Social/Forum |
-| `6` | Promotional/Advertisement |
-| `7` | Search/Directory/Bibliography |
-| `8` | Adult/Pornographic |
-| `9` | Personal/Misc |
-| `10` | Machine-Generated |
-| `11` | Legal/Regulatory |
-| `12` | Government/Political |
-| `13` | Literary/Creative |
-| `14` | Reviews/Critiques |
-| `15` | E-Commerce/Marketplace |
-| `16` | Images/Videos/Audio |
-| `17` | Other/Unclassified |
+| Code | Label | Examples |
+|------|-------|----------|
+| `-1` | Abstain | Unable to classify |
+| `1` | News/Editorial | CNN articles, opinion columns |
+| `2` | Academic/Research | ArXiv papers, research articles |
+| `3` | Reference/Encyclopedic/Educational | FAQs, Wikipedia entries |
+| `4` | Code/Software | GitHub repos, code examples |
+| `5` | Social/Forum | Conversation threads, Q&A boards |
+| `6` | Promotional/Advertisement | Product pages, calls to action |
+| `7` | Search/Directory/Bibliography | Link pages, search results |
+| `8` | Adult/Pornographic | Adult content |
+| `9` | Personal/Misc | Blogs, user profiles |
+| `10` | Machine-Generated | Lorem ipsum, garbled text |
+| `11` | Legal/Regulatory | Contracts, terms of service |
+| `12` | Government/Political | Legislation, press releases |
+| `13` | Literary/Creative | Poems, short stories |
+| `14` | Reviews/Critiques | Film critiques, product reviews |
+| `15` | E-Commerce/Marketplace | eBay listings, Amazon pages |
+| `16` | Images/Videos/Audio | YouTube videos, Imgur pages |
+| `17` | Other/Unclassified | Documents that resist classification |
 
 ### Document Type v2
-Updated format and structure classification:
+Updated classification based on WebOrganizer taxonomy with refined categories:
 
 | Component | Description | Path |
 |-----------|-------------|------|
@@ -161,38 +175,20 @@ Updated format and structure classification:
 | Secondary Code | Alternative document type code (v2) | `eai_taxonomy.document_type_v2.secondary.code` |
 | Secondary Label | Alternative document type label (v2) | `eai_taxonomy.document_type_v2.secondary.label` |
 
-**Possible Values:**
-| Code | Label |
-|------|-------|
-| `-1` | Abstain |
-| `1` | About (Org.) |
-| `2` | About (Personal) |
-| `3` | Academic Writing |
-| `4` | Audio Transcript |
-| `5` | Comment Section |
-| `6` | Content Listing |
-| `7` | Creative Writing |
-| `8` | Documentation |
-| `9` | FAQ |
-| `10` | Knowledge Article |
-| `11` | Legal Notices |
-| `12` | Listicle |
-| `13` | News (Org.) |
-| `14` | News Article |
-| `15` | Nonfiction Writing |
-| `16` | Personal Blog |
-| `17` | Product Page |
-| `18` | Q&A Forum |
-| `19` | Spam / Ads |
-| `20` | Structured Data |
-| `21` | Customer Support |
-| `22` | Truncated |
-| `23` | Tutorial |
-| `24` | User Review |
-| `25` | Other/Unclassified |
+**Selected Values:**
+| Code | Label | Examples |
+|------|-------|----------|
+| `3` | Academic Writing | Research papers, abstracts |
+| `7` | Creative Writing | Song lyrics, novel excerpts |
+| `8` | Documentation | API docs, README files |
+| `10` | Knowledge Article | Wikipedia, Britannica |
+| `14` | News Article | Newspaper articles, CNN content |
+| `18` | Q&A Forum | Quora, Stack Exchange |
+| `23` | Tutorial | Cooking recipes, WikiHow pages |
+| `25` | Other/Unclassified | Documents that resist classification |
 
 ### Extraction Artifacts
-Technical extraction quality indicators:
+Assessment of technical extraction quality, identifying issues from HTML-to-text conversion:
 
 | Component | Description | Path |
 |-----------|-------------|------|
@@ -202,17 +198,17 @@ Technical extraction quality indicators:
 | Secondary Label | Alternative extraction artifact label | `eai_taxonomy.extraction_artifacts.secondary.label` |
 
 **Possible Values:**
-| Code | Label |
-|------|-------|
-| `-1` | Abstain |
-| `0` | No Artifacts |
-| `1` | Leftover HTML |
-| `2` | Text Extraction Errors |
-| `3` | Irrelevant Content |
-| `4` | Indeterminate |
+| Code | Label | Description |
+|------|-------|-------------|
+| `-1` | Abstain | Unable to determine |
+| `0` | No Artifacts | Clean text with no leftover HTML or irrelevant elements |
+| `1` | Leftover HTML | HTML/code artifacts remaining after extraction |
+| `2` | Text Extraction Errors | Broken math expressions, encoding errors, improperly parsed tables |
+| `3` | Irrelevant Content | Headers, footers, nav menus extracted by mistake |
+| `4` | Indeterminate | Insufficient content to judge |
 
 ### Missing Content
-Content completeness assessment:
+Assessment of content completeness and extraction success:
 
 | Component | Description | Path |
 |-----------|-------------|------|
@@ -222,24 +218,26 @@ Content completeness assessment:
 | Secondary Label | Alternative missing content label | `eai_taxonomy.missing_content.secondary.label` |
 
 **Possible Values:**
-| Code | Label |
-|------|-------|
-| `-1` | Abstain |
-| `0` | No missing content |
-| `1` | Truncated Snippets |
-| `2` | Click Here References |
-| `3` | Incoherent Flow |
-| `4` | Missing Images or Figures |
-| `5` | Missing Referenced Data |
-| `6` | Indeterminate |
+| Code | Label | Description |
+|------|-------|-------------|
+| `-1` | Abstain | Unable to determine |
+| `0` | No Missing Content | Complete and coherent text |
+| `1` | Truncated Snippets | Obvious "...", incomplete paragraphs, cut-off text |
+| `2` | Click Here References | "Download here", "Click here" without linked content |
+| `3` | Incoherent Flow | Unreadable or illogical flow due to missing context |
+| `4` | Missing Images or Figures | Placeholders or references to missing visual content |
+| `5` | Missing Referenced Data | References to absent tables/datasets (e.g., "See Table 3") |
+| `6` | Indeterminate | Insufficient content to judge |
 
 </details>
 
 <details>
 <summary><strong>Content Quality Dimensions</strong></summary>
 
+Quality assessment inspired by NaturalReasoning and FineWeb efforts to categorize web data by information sophistication.
+
 ### Reasoning Depth
-Complexity of logical reasoning:
+Assesses the complexity and sophistication of logical reasoning in the document:
 
 | Component | Description | Path |
 |-----------|-------------|------|
@@ -249,18 +247,18 @@ Complexity of logical reasoning:
 | Secondary Label | Alternative reasoning depth label | `eai_taxonomy.reasoning_depth.secondary.label` |
 
 **Possible Values:**
-| Code | Label |
-|------|-------|
-| `-1` | Abstain |
-| `1` | No Reasoning |
-| `2` | Basic Reasoning |
-| `3` | Intermediate Reasoning |
-| `4` | Advanced Reasoning |
-| `5` | Exceptional Reasoning |
-| `6` | Indeterminate |
+| Code | Label | Description |
+|------|-------|-------------|
+| `-1` | Abstain | Unable to determine |
+| `1` | No Reasoning | Facts present but no evidence of reasoning |
+| `2` | Basic Reasoning | Basic analysis with minimal explanation and summarization |
+| `3` | Intermediate Reasoning | Some logical steps connecting ideas and structured thinking |
+| `4` | Advanced Reasoning | Multi-step reasoning and thorough analysis with well-developed explanations |
+| `5` | Exceptional Reasoning | Novel abstractions, theoretical frameworks, long chain-of-thought, original insights, or proofs |
+| `6` | Indeterminate | Insufficient context to judge |
 
 ### Technical Correctness
-Accuracy of technical information:
+Evaluates the accuracy and precision of technical information:
 
 | Component | Description | Path |
 |-----------|-------------|------|
@@ -270,18 +268,18 @@ Accuracy of technical information:
 | Secondary Label | Alternative technical correctness label | `eai_taxonomy.technical_correctness.secondary.label` |
 
 **Possible Values:**
-| Code | Label |
-|------|-------|
-| `-1` | Abstain |
-| `1` | Technically Flawed |
-| `2` | Partially Correct |
-| `3` | Mostly Correct |
-| `4` | Highly Correct |
-| `5` | Exceptionally Correct |
-| `6` | Not Applicable/Indeterminate |
+| Code | Label | Description |
+|------|-------|-------------|
+| `-1` | Abstain | Unable to determine |
+| `1` | Technically Flawed | Significant errors undermining content validity |
+| `2` | Partially Correct | Some correctness but contains flaws, omissions, or errors |
+| `3` | Mostly Correct | Technical correctness with minor flaws or incomplete explanations |
+| `4` | Highly Correct | High technical correctness with precise definitions and clear explanations |
+| `5` | Exceptionally Correct | Exceptional technical correctness with formal proofs and flawless content |
+| `6` | Not Applicable/Indeterminate | No technical content or insufficient context |
 
 ### Education Level
-Appropriate educational grade level:
+Assesses the appropriate educational background required to comprehend the content:
 
 | Component | Description | Path |
 |-----------|-------------|------|
@@ -291,27 +289,20 @@ Appropriate educational grade level:
 | Secondary Label | Alternative education level label | `eai_taxonomy.education_level.secondary.label` |
 
 **Possible Values:**
-| Code | Label |
-|------|-------|
-| `-1` | Abstain |
-| `1` | General Audience |
-| `2` | High School Level |
-| `3` | Undergraduate Level |
-| `4` | Graduate/Expert Level |
-| `5` | Indeterminate |
+| Code | Label | Description |
+|------|-------|-------------|
+| `-1` | Abstain | Unable to determine |
+| `1` | General Audience | Accessible to anyone with basic literacy; simple terms |
+| `2` | High School Level | Requires high school education; specialized terminology explained for non-experts |
+| `3` | Undergraduate Level | Requires college education; uses specialized terminology and assumes background knowledge |
+| `4` | Graduate/Expert Level | Requires graduate education or domain expertise; assumes deep background knowledge |
+| `5` | Indeterminate | Insufficient content to judge educational level |
 
 </details>
 
 <details>
 <summary><strong>Schema Structure</strong></summary>
 
-## Core Fields
-
-| Field | Type | Description | Path |
-|-------|------|-------------|------|
-| `id` | `Int64` | Unique identifier for each document | `id` |
-| `text` | `String` | The main textual content of the document | `text` |
-
 ## Metadata Structure
 
 The `metadata` field contains a nested structure with web archive information:
@@ -423,82 +414,6 @@ Domain and content type classification probabilities:
 
 </details>
 
-<details>
-<summary><strong>Data Provenance</strong></summary>
-
-All documents originate from web crawls with full WARC metadata preservation, enabling:
-- Source verification and attribution
-- Temporal analysis of web content
-- Content deduplication across crawls
-- Quality assessment pipeline reconstruction
-
-</details>
-
-<details>
-<summary><strong>Usage Examples</strong></summary>
-
-**Filter by quality score:**
-```python
-df.filter(df["quality_signals.red_pajama_v2.rps_doc_stop_word_fraction"] > 0.3)
-```
-
-**Filter by domain:**
-```python
-df.filter(df["metadata.source_domain"].contains("wikipedia"))
-```
-
-**Filter by education level:**
-```python
-df.filter(df["eai_taxonomy.education_level.primary.code"] == "2")  # High School Level
-```
-
-**Filter by content type:**
-```python
-df.filter(df["quality_signals.fasttext.eai_web_code"] > 0.8)
-```
-
-**Filter by document quality:**
-```python
-df.filter(
-    (df["quality_signals.red_pajama_v2.rps_doc_word_count"] > 100) &
-    (df["quality_signals.red_pajama_v2.rps_doc_stop_word_fraction"] > 0.2) &
-    (df["quality_signals.red_pajama_v2.rps_doc_frac_unique_words"] > 0.3)
-)
-```
-
-**Filter by reasoning depth:**
-```python
-df.filter(df["eai_taxonomy.reasoning_depth.primary.code"].isin(["4", "5"]))  # Advanced or Exceptional
-```
-
-**Filter by document type:**
-```python
-df.filter(df["eai_taxonomy.document_type_v2.primary.code"] == "3")  # Academic Writing
-```
-
-**Filter high-quality educational content:**
-```python
-df.filter(
-    (df["eai_taxonomy.education_level.primary.code"].isin(["2", "3"])) &  # High School or Undergraduate
-    (df["eai_taxonomy.technical_correctness.primary.code"].isin(["4", "5"])) &  # Highly or Exceptionally Correct
-    (df["eai_taxonomy.extraction_artifacts.primary.code"] == "0") &  # No Artifacts
-    (df["quality_signals.fasttext.fineweb_edu_approx"] > 0.7)
-)
-```
-
-</details>
-
-<details>
-<summary><strong>Usage Notes</strong></summary>
-
-- **Quality Filtering**: Use Red Pajama v2 metrics for content quality thresholds
-- **Domain Selection**: Leverage FastText scores for domain-specific filtering  
-- **Educational Applications**: Utilize EAI taxonomy for curriculum-aligned content selection
-- **Deduplication**: Apply n-gram duplication metrics for corpus cleaning
-- **Attribution**: WARC metadata enables proper source citation
-
-</details>
-
 ## How to Load the Dataset
 
 This section provides examples of how to load the `Research-EAI/eai-taxonomy-math-w-fm` dataset using different Python libraries and frameworks.
@@ -629,8 +544,4 @@ If you use this dataset, please cite our EssentialWeb paper:
   author={[Authors]},
   year={2025}
 }
-```
-
----
-
-*Part of the EssentialWeb ecosystem: Making dataset curation accessible, interpretable, and efficient.*
+```